Carlos A. Coello-Coello; Julie Greensmith; Natalio Krasnogor; Pietro Liò; Giuseppe Nicosia; Mario Pavone Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2012) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Emilia Tantar; Alexandru-Adrian Tantar; Pascal Bouvry; Pierre Del Moral; Pierrick Legrand; Carlos A. Coello Coello; Schütz Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2012) Saatavuus: Tilaustuote Kovakantinen kirja
Emilia Tantar; Alexandru-Adrian Tantar; Pascal Bouvry; Pierre Del Moral; Pierrick Legrand; Carlos A. Coello Coello; Schütz Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2014) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Kalyanmoy Deb (ed.); Erik Goodman (ed.); Carlos A. Coello Coello (ed.); Kathrin Klamroth (ed.); Kaisa Miettinen (ed.); Most Springer (2019) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Swagatam Das (ed.); Snehanshu Saha (ed.); Carlos A. Coello Coello (ed.); Jagdish Chand Bansal (ed.) Springer (2023) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Swagatam Das (ed.); Snehanshu Saha (ed.); Carlos A. Coello Coello (ed.); Jagdish C. Bansal (ed.) Springer (2024) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Swagatam Das (ed.); Snehanshu Saha (ed.); Carlos A. Coello Coello (ed.); Jagdish C. Bansal (ed.) Springer (2024) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Springer Sivumäärä: 800 sivua Asu: Kovakantinen kirja Painos: 2 Julkaisuvuosi: 2007, 18.09.2007 (lisätietoa) Kieli: Englanti
Solving multi-objective problems is an evolving effort, and computer science and other related disciplines have given rise to many powerful deterministic and stochastic techniques for addressing these large-dimensional optimization problems. Evolutionary algorithms are one such generic stochastic approach that has proven to be successful and widely applicable in solving both single-objective and multi-objective problems.
This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems, including test suites with associated performance based on a variety of appropriate metrics, as well as serial and parallel algorithm implementations.
